The Study of Stability and Structure of the Interaction Between β-Carotene Compounds with Methanol, Ethanol, Acetone, Chloroform, Carbon Tetrachloride, Cyclohexane, and N-Hexane using the Hartree-Fock and the Density Functional Theory Method

The purpose of this study was to determine the stability and structure on the interaction between β-carotene compounds with methanol, ethanol, acetone, chloroform, carbon tetrachloride, cyclohexane, and n-hexane compounds. This research is a molecular modeling using computational chemistry calculations with the function/basis set RHF/3-21G and B3LYP/3-21G. The computational chemistry calculations used Gaussian 09 Revision D 01 and visualization used the Jmol and Avogadro software. The data obtained from computational chemistry calculations with the function/basis set RHF/3-21G on the interaction between β-carotene -methanol compounds are ΔE = -11.899 kJ / mol, β-carotene -ethanol ΔE = -12.256 kJ/mol, β-carotene -acetone ΔE = -9.276 kJ/mol, β-carotene -chloroform ΔE = 5.262 kJ/mol, β-carotene -carbon tetrachloride ΔE = 3.747 kJ/mol, β-carotene-cyclohexane ΔE = 2.691 kJ/mol, β-carotene-n-hexane ΔE = 6.453 kJ/mol. The data obtained with the function/basis set B3LYP/3-21G on the interaction between β-carotene-methanol compounds are ΔE = -24.588 kJ/mol, β-carotene -ethanol ΔE = -25.123 kJ/mol, β-carotene -acetone ΔE = -18.140 kJ/mol, β-carotene -chloroform ΔE = 2.255kJ/mol, β-carotene -carbon tetrachloride ΔE = -1.187 kJ/mol, β-carotene-cyclohexane ΔE = -0.801 kJ/mol, β-carotene -hexane ΔE = -0.412 kJ/mol. Based on the analysis of thermodynamic data from computational chemistry calculations with the function / basis set UHF/3-21G and B3LYP/3-21G, it was found that β-carotene-ethanol and β-carotene-methanol mixtures had very stable mixtures.


Introduction
Palm oil is the largest source of vegetable oil needed by many industries in the world. In addition, the world demand for palm oil continues to grow by 5 percent per year. The fulfillment of world palm oil demand is dominated by Indonesian production. Indonesia produces about 43 percent of the total production of crude palm oil (CPO) in the world. The growth of palm oil production in Indonesia, which is 7.8 percent per year, is also better than Malaysia's which is 4.2 percent per year. Sumatra makes a very large contribution as a producer of palm oil, where 70% of palm oil production is produced on the island of Sumatra, followed by Kalimantan at 26% and the remaining 4% is produced from Sulawesi, Papua and Java. Seeing the mapping of oil palm producers, it is still possible to increase the amount of production, in addition to increasing the added value from the sale of palm oil products. So far, the products exported by Indonesia are still in the form of CPO, where the CPO can still be processed into semi-finished or finished materials [1].
Oil palm has a variety of uses to meet various human needs. One of the benefits of palm oil is palm oil, which is one of the most needed foodstuffs by humans. Palm oil has several advantages, including beta carotene as pro-vitamin A and vitamin E [2,3]. Quantitatively palm oil contains 96.2% neutral lipids; 2.4% phospholipids; 1.4% glycolipid and also contains unsophisticated fraction which is rich in carotenoids and tocopherols. Carotenoids can function as provitamin A and antioxidants, while tocopherol has activity as vitamin E and is an antioxidant substance [4]. Carotein compounds are very useful in human life [5].
In an effort to optimize the use of CPO, β-carotene and α-tocopherol were separated by extraction method. An important step in the extraction of β-carotene and α-tocopherol is the determination of the suitable solvent for these compounds. Several solvent extraction methods on the partition coefficient of carotenoids and tocopherols [6].Prá [7] extracted bioactive compounds from palm oil press fibers using different compressed fluids. Supercritical fluid extraction of tocopherol compounds from crude palm oil using CO2 solvents [8,9]. Extraction methods of carotene (α-and β-carotene) and tocols (α-tocopherol, α-, γ-, and δ-tocotrienol) from crude palm oil olein using ethyl lactate (EL) and ethanol (EtoL) in a temperature controlled mixer system -settler [10,11]. Pressurized liquid extraction (PLE) together with normal phase liquid chromatography (NPLC) was evaluated as a new approach for the determination of carotene and vitamin E isomers in residual oil obtained from palm compressed fiber (PPF) [12]. One method that can be done is using computational chemical methods through molecular modeling. The results obtained from this computational chemistry method are interaction data between molecules in the form of thermodynamic data. In this research, computational chemical calculations will be carried out on the interaction of several solvents with β-carotene and α-tocopherol compounds. The solvents that will be used are ethanol, methanol, acetone, chloroform, n-hexane, cyclohexane, and carbon tetrachloride.
Simulations of calculating the amount of molecular energy using a computer program are usually done by calculating the energy of the molecules regardless of their environment. In reality, there is never a single molecule in a single state but the number is very large and surrounded by other molecules as a solvent. In order to get closer to the real conditions, various efforts were made, including by considering the influence of the solvent. Several computer simulation studies to date have taken into account the presence of solvents in calculating molecular energies.
Yin [13] has determined the amount of energy involving the solvent as the environment of the reaction using a hybrid approach between Quantum Mechanics (QM) and Molecullar Mechanic (MM). In the calculation, the Potential Energy Surface (PES) method using Quasi Trajectory (QCT) and Time-Dependent Wave Packet (TDWP) was used by Jorfi [14]. Theoretical studies of the energy in the molecules that form clusters have been carried out based on the ab initio molecular orbital theory using the Hartree-Fock theory (HF) and Møller -Plessetparturbation theory [15]. Based on research conducted by Tewari [16], the effect of solvation and solvent polarization was calculated using the Polarizable Continum Model (PCM) and the Self-Consistent Isodensity Polarizable Continum Model (SCI-PCM). To describe the interaction between anions and water molecules using the Crooks fluctuation relationship to determine the effect of quantum on the free energy of dissociation in I-(H 2 O) ions and the average force of Na + (H 2 O) 12 evaluated using the Jurzinsky theorem [17].

Method
This research is a theoretical study using quantum mechanical theory on the interactions between molecules through molecular modeling. Computational chemistry calculations using Gaussian 09 Revision D 01 [18]. Computational chemistry calculations are used to determine the amount of molecular energy and energy in the interactions between molecules. The results of computational chemistry calculations were visualized using Jmol [19] software. The method used in computational chemistry calculations is the HF (UHF) and DFT (B3LYP) method with the basis set3-21G.The association models observed were: ethanol -β-carotene; methanol -β-carotene; acetone -β-carotene; chloroform -β-carotene; n-hexane -β-carotene; cyclohexane -β-carotene; carbon tetrachloride -βcarotene.

Determination of the interaction between β-carotene compounds and solvents.
Based on the results of computational chemistry calculations using the RHF / 3-21G function / basis set, energy data is obtained, so that energy changes can be calculated in the interaction process between the two molecules. The smallest energy change of -12,256 kJ / mol is the interaction between β-carotene and ethanol, while the largest energy change is 6,453 kJ / mol is the interaction between βcarotene and n-hexane. This fact shows that the most stable pair is β-carotene and ethanol. The amount of total energy (E) calculated by computational chemistry with the function/basis set UHF/3-21G is shown in Table 1. Based on the results of computational chemistry calculations using the function/basis set B3LYP/3-21G, energy data is obtained, so that energy changes can be calculated in the interaction process between the two molecules. The smallest energy change of -24,588 kJ/mol is the interaction between β-carotene and ethanol, while the largest energy change is 2.255 kJ/mol, which is the interaction between β-carotene and chloroform. This fact shows that the most stable pair is β-carotene and ethanol. The amount of total energy (E) calculated by computational chemistry with the function/basis set B3LYP/3-21G is shown in Table 2.

The structure of the interaction between β-carotene compounds and solvents.
In addition to obtaining thermodynamic data, computational chemistry calculations obtain the structure of the visualization of computational chemistry calculations. This section describes the structure of the visualization results on the interaction between β-carotene compounds and solvents. The structure of the visualization results using Jmol software for interactions between β-caroteneacetone compounds is presented in Figure 1.   Figure 2, a visualization of the results of computational chemistry calculations on the interaction between β-carotene and carbontetrachloride. Although the carbon tetrachloride compound is non-polar, it can be seen in the figure that the Cl group of carbon tetra chloride approaches the H atom of the β-carotene compound. The structure of the visualization results using Jmol software for the interaction between β-carotene -CHCl3 compounds is presented in Figure 3. The Figure 3, a visualization of the results of computational chemistry calculations on the interaction between β-carotene and chloroform compounds. In the figure, it can be seen that the Cl group of chloroform approaches the H atom of the β-carotene compound.The structure of the visualization results using Jmol software for the interaction between β-carotene-ethanol compounds is presented in Figure 4. The Figure 4, a visualization of the results of computational chemistry calculations on the interaction between β-carotene and ethanol. In the figure, it can be seen that the O atom group of ethanol approaches the H atom of the β-carotene compound. The structure of the visualization results using Jmol software for interactions between β-carotene -hexane compounds is presented in Figure 5. In the Figure, a visualization of the results of computational chemistry calculations on the interaction between β-carotene and n-hexane. In the figure, it can be seen that the n-hexane compound is closer to the carbon chain of the β-carotene compound. This happens because n-hexane is non-polar and prefers to interact with non-polar carbon chains. The structure of the visualization results using Jmol software for the interaction between β-carotene -methanol compounds is presented in Figure 6. In the Figure, a visualization of the results of computational chemistry calculations on the interaction between β-carotene and methanol. In the figure, it can be seen that the O atom group of methanol approaches the H atom of the β-carotene compound. The structure of the visualization results using Jmol software for interactions between β-carotene -cyclohexane compounds is presented in Figure 7.  Figure 7, a visualization of the results of computational chemistry calculations on the interaction between β-carotene and cyclohexane. In the figure, it can be seen that the cyclohexane compound is closer to the carbon chain of the β-carotene compound. This happens because cyclohexane is non-polar and prefers to interact with non-polar carbon chains.